Data Scientist (Risk Intelligence)

Data Scientist (Risk Intelligence)

Location : Onsite New York, NY (5 days / week)

Position Type : Full-Time (Permanent)

Work Policy : In-person only (Relocation stipend available; visa sponsorship available)

Start Timeline : ASAP

About

This is a foundational data science hire within the Risk & Underwriting team. The Data Scientist will focus on developing and productionizing underwriting models, building risk dashboards, and driving portfolio analytics to support scaling of credit offerings while maintaining strong portfolio performance.

Why join

Join a high-impact role as one of the first data science hires in a fintech startup

Build risk intelligence systems powering credit decisions for e-commerce businesses

Collaborate closely with underwriting and product teams in a fast-paced, high-output environment

Opportunity to expand scope into broader intelligence / AI functions over time

Relocation stipend and visa sponsorship available for exceptional candidates

Compensation

Base Salary : $140,000 - $170,000 (flexible for senior candidates)

Equity : 0.05% - 0.10%

Tech environment

Languages : SQL, Python (or R)

Tools : Hex, Looker, Mode, Metabase

Focus areas : Underwriting models, credit risk analytics, portfolio monitoring, dashboards

Role summary

The Data Scientist will partner with underwriting to design, implement, and optimize credit risk models, monitoring tools, and automation workflows. The role requires a mix of strong technical skills, financial acumen, and the ability to operate as a generalist in a lean startup environment.

Responsibilities

Build dashboards, monitoring tools, and risk models

Automate underwriting and credit assessment workflows

Conduct back-testing and model tuning

Collaborate with underwriting to translate business needs into quantitative insights

Expand scope to broader intelligence / AI functions as the company grows

Must-have qualifications

4+ years of experience in data science, preferably in credit, underwriting, or financial services

Proficiency in SQL and Python (or R)

Strong background in statistics, machine learning, and data modeling

Experience with dashboards and data visualization tools (e.g., Hex, Looker, Mode, Metabase)

Strong communication skills and ability to operate in a generalist startup environment

Ability to work onsite in NYC 5 days / week (relocation possible)

Preferred qualifications

Experience in e-commerce lending or fintech startups with lending products

Exposure to both fintech and traditional banking environments

Understanding of financial KPIs and ecommerce / fintech datasets

Experience working closely with credit / risk or lending teams

Signals of excellence such as :

Prior experience building end-to-end solutions (side projects, startups, internal tools)

Past founder or community-building experience

Roles with high ownership or multiple hats

Experience in high-output environments such as Cash App, Square, or other top fintechs

Additional desired experience

Willingness to work long hours as needed in person in San Francisco

Experience with Docker, Kubernetes, and Terraform

Experience building for scale, ideally at companies where products are self-hosted by customers

Experience with hyperscalers (AWS, GCP, Azure), with a preference for multi-cloud experience

5+ years of experience as a DevOps or Infrastructure Engineer

Ability to work closely with customers, demonstrating patience and friendliness

High attention to detail

High agency and strong propensity to learn

B.S. in Computer Science or equivalent degree, undergraduate or higher

Experience at Series B+ stage companies or later, or smaller companies with very large-scale products

Experience with Linux systems is a plus

Strong background in computer networking